The goal of Question Answering over Knowledge Graphs (KGQA) is to retrieve the answer from a knowledge graph (KG) for a given natural language question.
A conventional solution to KGQA is to translate natural language questions to a formal query, which then returns the intended answer when executed over the KG.
The primary KGQA data sets, such as SimpleQuestion [1]}, WebQuestions [2]}, LC-QuAD [3]} and KGQA systems [4]} consider the formal query response as the final answer to the question.
KGQA challenges such as QALD [5]} consider the formal query or their response for evaluations.
However, these responses might leave the final end-user unsatisfied with the answer representation.
